• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.724-731
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• 2016

The purpose of this study was to determine what rules or patterns exist when people gaze at a villa savoye, which is probably Le Corbusier's best known building, using eye-movement tracking techniques. Villa savoye was designed, addressing his emblematic "Five Points", such as pilotis, functional roofs, free floor plans, long horizontal windows, and freely-designed facades. This study examined how the villa savoye's facade image is formed in an objective manner. This study selected a total of 56 test subjects, and showed them an image of a villa savoye. Using eye-movement tracking tools, this study recorded where they mostly gazed at when seeing the building. In addition, an experiment was carried out to test the different points of view, relating to visual attention, between the two groups with different levels of knowledge in architecture. To analyze the data, the Gaze Frequency was used as the key indicator. The results showed that the subjects have a higher degree of attention to either the door or window in general than in former studies. The architecture major group showed that they gazed the experiment image more evenly.

• Science of Emotion and Sensibility
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• v.19 no.1
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• pp.111-126
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• 2016

As the marketing value of Facebook advertisements increases, companies seek to create successful Facebook advertisements in order to promote their brands or products. This research aims to identify Facebook advertising factors that influence users' eye movements and attention, and thereby to investigate effective visual elements of Facebook advertising contents. Firstly, we identified two contributing factors influencing users' responses to Facebook advertisements: the formats of advertising contents(Text, Text in Image, and Movie) and the product properties(Involvement, Think/Feel). Based on theoretical reviews, eye tracking tests and surveys were conducted in order to examine how these two factors affect users' responses on Facebook, i.e. visual perception and users' purchasing responses. It was found that there were distinctive patterns of users' visual perceptions and purchasing behavioral responses according to the formats of the advertised contents. Meanwhile, the advertised products' properties influenced only the users' purchasing responses. Finally, the key findings of this research offer helpful guidelines for providers and developers to create effective SNS advertisements.

• Journal of the Korea Computer Graphics Society
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• v.16 no.3
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• pp.1-10
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• 2010

In this paper, we propose a novel noiseless method of BRDF rendering on a GPU in real-time. Illumination at a surface point is formulated as an integral of BRDF producted with incident radiance over the hemi-sphere domain. The most popular method to compute the integral is the Monte Carlo method, which needs a large number of samples to achieve good image quality. But, it leads to increase of rendering time. Otherwise, a small number of sample points cause serious image noise. The main contribution of our work is a new importance sampling scheme producing a set of incoming ray samples varying continuously with respect to the eye ray. An incoming ray is importance-based sampled at different latitude angles of the eye ray, and then the ray samples are linearly connected to form a curve, called a thread. These threads give continuously moving incident rays for eye ray change, so they do not make image noise. Since even a small number of threads can achieve a plausible quality and also can be precomputed before rendering, they enable real-time BRDF rendering on the GPU.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.1-8
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• 2010

The researches about gaze recognition which current user gazes and finds the location have increasingly developed to have many application. The gaze recognition of existence all about researches have got problems because of using equipment that Infrared(IR) LED, IR camera and head-mounted of high price. This study propose and implement the gaze recognition system based on SVM using a single PC Web camera. The proposed system that divide the gaze location of 36 per 9 and 4 to recognize gaze location of 4 direction and 9 direction recognize user's gaze. Also, the proposed system had apply on image filtering method using difference image entropy to improve performance of gaze recognition. The propose system was implements experiments on the comparison of proposed difference image entropy gaze recognition system, gaze recognition system using eye corner and eye's center and gaze recognition system based on PCA to evaluate performance of proposed system. The experimental results, recognition rate of 4 direction was 94.42% and 9 direction was 81.33% for the gaze recognition system based on proposed SVM. 4 direction was 95.37% and 9 direction was 82.25%, when image filtering method using difference image entropy implemented. The experimental results proved the high performance better than existed gaze recognition system.

• Journal of Korean Ophthalmic Optics Society
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• v.8 no.1
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• pp.35-39
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• 2003

The display technology on the retina is the key role in inspecting the condition of the patients. 2-dimensional retina image is widely used in the eye examination as of today. Recently, 3-dimensional retina image ones have been introduced to this area, but the quality of the image is not fully satisfied to the operator. For the purpose of developing 3-D retina imaging instrument, the optimization of a 3-D retina imaging system using Code-V tool was investigated in this thesis. He-Ne laser having the wavelength 632.8 nm was used to make a power source to detect the retina. Several lenses and mirrors installed on sledge which were developed to perform focus control on 3-D device were designed to make a beam focusing and direct line. Polygon scanner having 24 mirror facets and galvanometer making tilting movement were utilized to make a 2-D laser plane. Also, design of eye ball had been fulfilled to see the focus of the 2-D plane. Reflected ray from retina detected on the sensor array with the same path. All cognitive components were optimized for aberration correction in order to focus on retina. Results of optimization were compared to those of initial designed optics system. On the basis of above results, the result of third aberration has been corrected to stable values to the optical system. MTF evaluating the resolution of an image has been closely correlated to the diffraction limit and PSF indicating the strength distribution of an image has shown the SR value as 0.9998 having high performance. The possibility of new and powerful 3-D retina image instrument was verified by simulating each component of the instrument by Code-V.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.283-288
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• 2001

In this paper, we proposed a method for extracting facial characteristics of human being in an image. Given a pair of gray level sample images taken with and without human being, the face of human being is segmented from the image. Noise in the input images is removed with the help of Gaussian filters. Edge maps are found of the two input images. The binary edge differential image is obtained from the difference of the two input edge maps. A mask for face detection is made from the process of erosion followed by dilation on the resulting binary edge differential image. This mask is used to extract the human being from the two input image sequences. Features of face are extracted from the segmented image. An effective recognition system using the discrete wave let transform (DWT) is used for recognition. For extracting the facial features, such as eyebrows, eyes, nose and mouth, edge detector is applied on the segmented face image. The area of eye and the center of face are found from horizontal and vertical components of the edge map of the segmented image. other facial features are obtained from edge information of the image. The characteristic vectors are extrated from DWT of the segmented face image. These characteristic vectors are normalized between +1 and -1, and are used as input vectors for the neural network. Simulation results show recognition rate of 100% on the learned system, and about 92% on the test images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.335-340
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• 2011

This study evaluated anti-wrinkle effect for eye using essence and cream containing extract of Liriope platy phyllla, Inonotus obliquus, Glycyrrhiza glabra, black ginseng, Atractylodes japonica, Poria cocos Wolf, Angelica gigas, Rehmanniae Radix Preparata and Cnidii Rhizoma, Paeonia lactiflora. 6 female adults on average at the age of 44.8, applied cream after essence under the normal conditions of use on the crow's feet area, twice a day (in the morning and evening), 2mg/$1cm^2$ for 4weeks. After 4 weeks, the replica of eye wrinkle was made and analyzed the image. The result was that eye wrinkle was decreased in R1($3.22{\pm}0.85$ to $2.38{\pm}0.32$), R2($3.08{\pm}0.83$ to $2.22{\pm}0.32$), R3($2.29{\pm}0.64$ to $2.29{\pm}0.64$), R4($0.44{\pm}0.14$ to $0.44{\pm}0.14$), and R5($0.98{\pm}0.21$ to $0.98{\pm}0.21$)(P<0.05). Therefore, oriental medicine cosmetics containing traditional herb medicine may play a role anti-wrinkle for eye.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.255-264
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• 2011

In this paper, we propose a forward vehicle detection algorithm using column detection and bird's-eye view mapping based on stereo vision. The algorithm can detect forward vehicles robustly in real complex traffic situations. The algorithm consists of the three steps, namely road feature-based column detection, bird's-eye view mapping-based obstacle segmentation, obstacle area remerging and vehicle verification. First, we extract a road feature using maximum frequent values in v-disparity map. And we perform a column detection using the road feature as a new criterion. The road feature is more appropriate criterion than the median value because it is not affected by a road traffic situation, for example the changing of obstacle size or the number of obstacles. But there are still multiple obstacles in the obstacle areas. Thus, we perform a bird's-eye view mapping-based obstacle segmentation to divide obstacle accurately. We can segment obstacle easily because a bird's-eye view mapping can represent the position of obstacle on planar plane using depth map and camera information. Additionally, we perform obstacle area remerging processing because a segmented obstacle area may be same obstacle. Finally, we verify the obstacles whether those are vehicles or not using a depth map and gray image. We conduct experiments to prove the vehicle detection performance by applying our algorithm to real complex traffic situations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.75-83
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• 2008

We propose a welfare interface using multiple fecial features tracking, which can efficiently implement various mouse operations. The proposed system consist of five modules: face detection, eye detection, mouth detection, facial feature tracking, and mouse control. The facial region is first obtained using skin-color model and connected-component analysis(CCs). Thereafter the eye regions are localized using neutral network(NN)-based texture classifier that discriminates the facial region into eye class and non-eye class, and then mouth region is localized using edge detector. Once eye and mouth regions are localized they are continuously and correctly tracking by mean-shift algorithm and template matching, respectively. Based on the tracking results, mouse operations such as movement or click are implemented. To assess the validity of the proposed system, it was applied to the interface system for web browser and was tested on a group of 25 users. The results show that our system have the accuracy of 99% and process more than 21 frame/sec on PC for the $320{\times}240$ size input image, as such it can supply a user-friendly and convenient access to a computer in real-time operation.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.261-282
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• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.